Throughout his career, Drew has sought to better understand the mind and its processes by applying a mathematically-focused lens to questions about behavior and cognition. As an undergraduate, he worked with Professor Rimvydas Baltaduonis at Gettysburg College on experimental economics projects, including an honors thesis on the effect of prediction markets on information cascade-prone environments. After a short time in the financial industry, Drew became a cook and chef in some of New York City’s finest Michelin-starred restaurants.

Combining all of these previous experiences, Drew is now a PhD candidate at The Graduate Center, CUNY in the Cognitive and Comparative Psychology program. His advisor is Professor Matthew Crump, and he works in the Computational Cognition Lab focused on computational models of cognitive processes and experimental psychology. Drew also works part-time as a Data Scientist at Marina Maher Communications where his work includes hierarchical modeling, full-stack app development, and much more.

Download my resumé.

  • Computational Models of Cognition
  • Cognitive Recommender Systems
  • Bayesian Statistics
  • PhD Candidate in Cognitive and Comparative Psychology, 2027

    The Graduate Center, CUNY

  • BA in Economics, 2011

    Gettysburg College


The Graduate Center, CUNY
Graduate Assistant
The Graduate Center, CUNY
Aug 2021 – Present New York City

Responsibilities include:

  • Developed, designed, and programmed cognitive science experiments to better understand the effects of image dimensionality on memory.
  • Developed and programmed an R package focused on building repeatable MINERVA II models quickly and efficiently.
  • Led literature review discussions focused on a broad array of topics including Bayesian data analysis, latent semantic analysis, and principal components analysis.
Marina Maher Communications
Data Scientist
Marina Maher Communications
Mar 2020 – Present New York City

Responsibilities include:

  • Supervised a team of two Junior Data Scientists across multiple long-term and short-term projects.
  • Developed and implemented an expected loss methodology to determine optimal stopping points in A/B testing.
  • Utilized natural language processing and sentiment analysis on unstructured text survey responses.
  • Developed a hierarchical Bayesian model to forecast engagement on social media influencers’ content.
  • Created real-time, interactive dashboards using Plotly Dash, AWS App Runner, and AWS Athena for Fortune 500 clients.
Kepler Group
Senior Analyst, Marketing Analytics
Kepler Group
Jan 2018 – Mar 2020 New York City

Responsibilities include:

  • Supervised a team of two analysts across multiple client teams.
  • Developed and implemented A/B testing methodology utilizing Bayesian inference.
  • Utilized SQL and the Python to query, analyze, and model panel, time series, and cross-sectional data.
  • Developed and implemented department-wide statistics trainings, including A/B testing and linear and multivariate regression.